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Record W4285728255 · doi:10.1680/jenes.21.00051

Adsorption of dye using natural clay from water

2022· article· en· W4285728255 on OpenAlexvenueno aff
Mohammed Bourouiss, Mustapha Djebbar, Ftiha Djafri

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsnot available
Fundersnot available
KeywordsMontmorilloniteAdsorptionFreundlich equationLangmuirMethylene blueChemistrySodiumClay mineralsNuclear chemistryInorganic chemistryMineralogyOrganic chemistry

Abstract

fetched live from OpenAlex

Removal of the dye methylene blue from water at different concentrations, adsorbent pH values and times was investigated. Natural clay was treated by cation exchange, which was confirmed by X-ray diffraction and infrared spectroscopy analyses. The experimental results showed that a high pH promotes adsorption. The adsorption isotherms are described by the equations of Langmuir and Freundlich isotherms. It is important to note that the quantity of calcium oxide (CaO) corresponding to calcite is higher in natural clay (9.7% by weight) compared to sodium (Na) montmorillonite fraction (2.01% by weight). This clearly shows that the clay d hkl spacing increased from d = 13.58 Å to d = 17 Å, which could be attributed to natural clay and sodium montmorillonite, which confirms good clay purification. The maximum capacities of dyes adsorbed on natural clay and sodium montmorillonite (Q max) are 142.85–250 and 80–277.77 mg/g, respectively. The correlation coefficients R 2 = 0.99 of the Freundlich and Langmuir models for natural clays and sodium montmorillonite have the same values. This indicates that the two models are the best for the adsorption of the dye methylene blue on natural clay and sodium montmorillonite.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.187
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

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